Design of a PD Controller Combined with a MRAS-Based LFFC for a Two - Link Robot Manipulator

Abstract:

In this paper we introduce a new control structure which consists of a PD controller and a Model Reference Adaptive System-based Learning Feed-Forward Controller to a two-link robot manipulator. The proposed approach seeks to benefit the multi-variable control of multi-input multi-output systems with variable parameters, nonlinear behavior, and significant coupling in the system dynamics. Conventionally, the function approximators with standard neural networks were used which enabled to approximate complex non-linear functions. The idea of LFFC is applied but without using the complex neural networks. Instead, we propose to use MRAS-based adaptive components. The well-known Lyapunov approach is used to find stable adaptive laws for the feed-forward parameters in such way that learning converges. The effectiveness of the proposed approach is demonstrated by simulation analysis.

• Periodical: Applied Mechanics and Materials (Volumes 541-542)
• Pages: 1102-1106
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.541-542.1102
• Online since: March 2014
• Authors: Nguyen Duy Cuong, Nguyen Van Lanh, Dam Bao Loc, Tran Que Son, Ngo Minh Chu
• Keywords: Learning Feed-Forward Control (LFFC), Model Reference Adaptive Systems (MRAS), Multi-Input Multi-Output (MIMO) System, Two–Link Robot Manipulator

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